Decision-support Tool For Is Investment

Expanding the Knowledge Economy: Issues, Applications, Case Studies Paul Cunningham and Miriam Cunningham (Eds) IOS Press, 2007 Amsterdam ISBN 978-1-58603-801-4

i-Transformation in Swiss Companies: a Decision-Support Tool for Small and Midsize Enterprises Philipp ZIMMERMANN, Fabrice HOLZER University of Applied Sciences – Western Switzerland, TECHNO-pôle 5, Sierre, 3960, Switzerland Tel: + 41 27 6069035, Fax: + 41 27 6069000, Email: {philipp.zimmermann, fabrice.holzer}@hevs.ch Abstract: Nowadays, almost any kind of enterprise is facing the challenge of information- and communication technology (ICT) investment issues. However, taking the appropriate ICT-investment decisions is often beyond the Small and Midsize Enterprises’ (SME) decision-makers. Current research struggles with an easy-to-use methodology that helps identifying the technologies able to provide a real value-added to the enterprise. At this aim, the present paper intends to fill the gap by proposing a decision-support tool for Chief Information Officers of SMEs. By focusing intentionally and exclusively on information systems (IS), this tool gives tangible investment recommendations based on both the enterprise’s current level of IS-acquisition and its respective financial return. Finally, we plan to offer a benchmark "cockpit" able to compare the results of each enterprise with its competitors in order to identify necessary steps towards an optimal level of technology implementation.

1.

Introduction

At the present time enterprise investments in information and communication technologies (ICTs) appear to be manifest and necessary, since they are commonly suspected to increase organizational efficiency, quality and transparency [1,2]. However, current statistics show that these investments are not always reflected in terms of increased productivity and benefits in the companies’ accounting statements, particularly in those of small and midsize enterprises (SME). This paradoxical situation can be best illustrated with the example of Swiss enterprises: For several successive years, Switzerland was ranked on the top of international ICT-expenditure statistics. According to the European Information Technology Observatory [3], Switzerland presents an expenditure average per capita of 2673 Euros in 2004, followed by Sweden with 2374 Euros, the USA (1966) and the UK (1908); with 1565 Euros, Ireland is almost in the Western European average of 1521 Euros. However, as a recent study of the OECD [4] shows, these important ICT-investments do oftentimes not result in increased productivity for Swiss enterprises. This study analyzed the contribution of ICTs on labour productivity growth in 14 European countries and the US from 1996-2002. The results of this study show that Ireland and the USA recorded the most important contribution of the ICTs to labour productivity growth in that period (1.9 percentage points in both countries), followed by Finland (1.40), Sweden (1.33) and the UK (1.21). In Switzerland, the contribution of the ICTs to labour productivity growth is only of 0.43 percentage points, ranking it on the 11th position out of the 15 analyzed countries. But despite these results, several Swiss enterprises such as Swissquote, Logitech or Dartfish use the ICTs in such a way, it modifies existing business models and substantially increases their performance [5], i.e. they are able to convert the use of their technologies Copyright © 2007 The Authors

into real value-added. However, current research struggles with a methodology that helps decision-makers to clearly identify technologies effectively able to bring about increased productivity and lead to value-added for their enterprise.

2.

Objective

This paper explores the issues addressed in the previous section from both a theoretical and an empirical point of view. Following IBM’s CEO Samuel Palmisano assertion: “If you can’t measure it, you can’t manage it”, this paper finally aims at proposing a practical decision-support tool for SMEs, helping them to successfully realize their companies’ « itransformation », i.e to make the appropriate ICT-investment decisions that will effectively convert them into value added for their enterprise.

3.

Methodology

Through a literature review we will first propose an overview over the existing decisionsupport tools dealing with the alignment of ICT-strategies and business-strategies. In a second step, we will then develop a model of decision-support tool addressed to company managers. We will therefore focus more specifically on information systems (IS), by analyzing the enterprise’s current IS-investments and their impact on four major business dimensions. The results of this analysis will allow ranking the enterprise’s IS-priorities in a scatter diagram that has been conceived in analogy to the Boston Consulting Group’s growth-share matrix. On the basis of the current IS-investments and the financial return expected, this tool recommends appropriate IS-decisions, i.e. to invest in or to drop specific IS-categories. A final step in a near future is to offer a benchmark "cockpit" able to compare the results of each enterprise with its competitors in order to identify necessary steps towards an optimal level of technology implementation.

4.

State of the Art: Existing Decision-Support Tools

This section gives an overview over the main existing decision-support tools aimed at transforming or aligning business strategies with ICT-strategies. Current research fails to deliver a simple tool helping SMEs to transform their technological potential into real value-added. Nevertheless, there are basically two models pursuing similar objectives: 4.1 Venkatraman’s Strategic Alignment Model (SAM) In 1991 Morton and Venkatraman stated that organizations had to align their business objectives and the strategic technology objectives in order to successfully realize their itransformation [6,7]. Therefore, Venkatraman proposes his Strategic Alignment Model (SAM), which says that every enterprise should try to find an appropriate alignment strategy for the following four domains: 1. Business strategy is defined in terms of choices pertaining to the positioning of the business in the competitive product-market arena. 2. Organization infrastructure and processes is defined in terms of the choices pertaining to the particular internal arrangements and configurations that support the organization’s chosen position in the market. 3. IT strategy is defined in terms of choices pertaining to the positioning of the business in the IT marketplace and is analogous to the business strategy. 4. IS infrastructure and processes is defined in terms of choices pertaining to the internal arrangements that determine the data, applications, and technology infrastructure to deliver the required IT products and services. Every enterprise should decide on whether to focalize on one alignment alternative rather than on another according to their organizational and competitive context. By Copyright © 2007 The Authors

choosing to align a maximum of domains, the enterprise will reach a coherent and consistent result. 4.2 Forrester’s Method Based on an IT-Maturity Index Although not considered strictly speaking as a decision-support tool, Forrester Consulting proposed an approach based on an IT-maturity index that enterprises obtain from a selfevaluation by the CIO [8]; Forrester suggests that specific IT-investment strategies should be based on that self-evaluation and therefore proposes to combine an enterprise’s ITinvestments and IT-maturity data. This results in the following four possible combinations: • High IT-maturity/high IT-investment: Global firms in savagely competitive industries with high technology dependency spend a significant percentage of revenue on IT effectively. The degree to which their IT organizations have evolved will ensure that this spending is well-applied. • High IT-maturity /low IT-investment: More centralized, stable firms with relatively low IT spending but a high IT maturity will optimize their IT dollar, focusing on tuning existing IT spending rather than to consume resources for new investments. • Low IT-maturity/ low IT-investment: Firms that have few external forces driving IT investment spend few resources in IT; in addition, resources are wasted in redoing projects that did not deliver significant returns. • Low IT-maturity/high IT-investment: Some firms are caught in marketing effects, but they lack a solid set of IT practices that keep their projects under control. These firms thrash under the external pressures and waste money for on a large scale. In clear, each enterprise has to evaluate its own IT-maturity according to a set of predefined characteristics and compare this maturity to its actual IT-spending. This will indicate in which out of these four categories it takes place. According to this, it should then be possible to make appropriate decisions, knowing which specific technology to invest in. Both methods presented in this section, are not clearly dedicated and rather difficult to apply for decision-makers at SMEs, since they do not give any concrete recommendations which specific technology the enterprise should invest in and which technology should be dropped. In addition, those methods do not take into account best practice solutions or references of the branch. Therefore, our method tries to fill this gap by proposing a decision-support tool that gives concrete IS-investment recommendations based on a benchmark against competitors of the same branch.

5.

Proposition of a Decision-Support Tool for SMEs

This chapter presents the decision-support tool aimed at helping company managers to make appropriate IS-investment decisions that effectively lead to increased value-added for the enterprise. Therefore, a first and necessary step is to collect the necessary data about the SME’s current IS-investments and their respective economic return. 5.1

The i-Transformation Index

The tool presented in this paper starts with a presentation from a financial point of view of both enterprise’s IS-investments and the respective economic return over the entire product lifetime. More precisely, we propose the following assessment grid ( In this grid, the first column from the left contains the main existing categories of technologies. In order to clearly define the analyzed subject, this paper focuses on the various types of information systems (IS). Therefore, we follow Barron et al. [9], who structure computer-based information systems according to nine major categories: Table 1): Copyright © 2007 The Authors

In this grid, the first column from the left contains the main existing categories of technologies. In order to clearly define the analyzed subject, this paper focuses on the various types of information systems (IS). Therefore, we follow Barron et al. [9], who structure computer-based information systems according to nine major categories: Table 1: Artefact of the i-transformation index Total IS Costs/Total Expenses 1) Transaction Processing Systems (TPS) 2) Management Information Systems (MIS) 3) Office Automation Systems (OAS) 4) Decision Support Systems (DSS) 5) Expert Systems (ES) 6) Group Support Systems (GSS) 7) Knowledge Work Systems (KWS) 8) Executive Information Systems (EIS) 9) Strategic Information Systems (SIS)

11,4% 17,0% 8,4% 5,6% 2,8% 14,2% 8,4% 5,6% 11,4%

Product value-added Customer relationship (PVA) (CR)

Infrastructure / operations (IO)

Increase/decrease of product margin in %

Marginal sales turnover increase/decrease in %

Operational cost savings in %

65 55 -15 0 0 -5 -5 15 -40

50 -25 0 0 10 15 20 -20 0

0 -15 -20 50 40 35 0 25 -10

Financials (FI) Net return on investment (%) (= Benefits of the period / Invested capital)*100) 15 20 15 -10 -40 -30 40 35 60

1. Transaction Processing Systems (TPS) capture and process data resulting from business transactions such as orders, payments, invoices and sales. A TPS records data, but does little to convert data into information or knowledge. 2. Management Information Systems (MIS) supplement transaction processing systems with management reports required to plan, monitor, and control business operations. A MIS takes data recorded by a TPS and converts them into management information and presented in report form. 3. Office Automation Systems (OAS) combine various technologies to reduce the manual labor required in operating an effective office environment. A typical OAS handles and manages documents through word processing, desktop publishing, and digital filing, scheduling through electronic calendars, and communication through electronic mail, voice mail, or video conferencing. 4. Decision Support Systems (DSS) provide their users with decision-oriented information for decision making. A DSS typically focuses on the future, and is designed to help decision makers with unstructured decisions. 5. Expert Systems (ES) are an extension of decision support systems. An ES captures the knowledge, expertise and reasoning capabilities of a human expert and then simulates the ‘thinking’ of that expert. 6. Group Support Systems (GSS) permit people to process and interpret information as a group, even if they are not working face to face. Like a DSS, a GSS supports people working in situations that are not fully structured. 7. Knowledge Work Systems (KWS) aid knowledge workers in the creation and integration of new knowledge within an organization. 8. Executive Information Systems (EIS) provide critical information in easy-to-use displays to top and middle management. These systems cut across functional areas of the organization and provide access to external databases. 9. Strategic Information Systems (SIS) apply information technology to a firm’s products, service, or business processes to help it gain a strategic advantage over its competitors. The first line from the top of the proposed assessment grid focuses on the business dimensions impacted by the analyzed technologies. We understand a business model as a description of the value a company offers to its customers, the architecture of the firm and its network of partners for creating, marketing and delivering this value and relationship capital, in order to generate profitable and sustainable revenue streams [10]. Because a successful business model finally always results in increased financial benefits, the applied measures exclusively focus on tangible, financial measures. Similar to Osterwalder and Pigneur’s [10] e-business framework we will assess the economic return of the IS-investments on the following four major business dimensions: Copyright © 2007 The Authors

1. Product value-added: This dimension describes, what business the enterprise is in as well as the product innovation and the value proposition it offers on the market. The impact of the specific IS-categories on this dimension will be assessed using the product profitability, i.e. the increase/decrease of the product margin. 2. Customer relationship: This dimension specifies who the enterprise’s target customers are, how it delivers its products, and how it builds strong relationships with them. The impact on this dimension will be assessed by measuring the increase/decrease of the sales turnover generated by the additional number of customers compared to the average of the one generated by the previous customers’ portfolio. 3. Infrastructure/operations: This dimension describes how efficiently the enterprise performs infrastructure or logistics issues. The impact on this dimension will be assessed by measuring the IS-related operational cost savings. 4. Financials: Finally, this dimension specifies what the revenue model and the cost model are. The impact on this dimension will be assessed by measuring the net return of the investments for each IS-category. 5.2

The Decision-Support Tool for the Company Decision-Maker

On the basis of this « i-transformation index » each enterprise can then set its own ISpriorities. This assessment will be based on a simple matrix (based on the BCG’s growth share matrix), which will indicate the appropriate IS-strategy (invest, milk, outsource/drop) according to economic potential for each technology [11]. In analogy to this matrix, our decision-support tool suggests an appropriate IS-strategy according to the enterprise’s current IS-investments and the economic potential for each IS-category. Therefore, the scatter diagrams (Figure 1) rank the strategic options for each IS-category and for each of the dimensions outlined above on the basis of the most significant economic potential. Depending on the position in the box, one out of four types of strategies can be suggested: 1. A1 Cash cows: Strategy => Milk: Cash cows are IS with high economic returns which only require little financial investment. These IS typically generate cash in excess of the amount of cash needed to maintain them. Therefore, every company should like to own as many as possible and “milk” them continuously with as little investment as possible. 2. A2 Stars: Strategy => Invest: Stars are IS with a high economic return, but that also require relatively high investment. Although investing in this type of IS may require some cash, this is worthwhile considering the economic potential it represents. 3. B1 Dogs: Strategy => Drop: Dogs are IS with little economic return and that require important financial investments. These IS typically do not generate enough cash to be maintained or to be developed. Therefore, such a system is recommended not to be acquired. 4. B 2 Question marks: Strategy => Invest or drop/outsource: Question marks contain low economic potential, but because the enterprise already highly invested in these systems, it would be a luxury to abandon them. Therefore, question marks must be analyzed carefully in order to determine whether they are worth the investment required to maintain them. Thus the aim of this tool is to indicate, where to apply initial effort for maximized effects, i.e. to identify IS-priorities with the most significant economic potential for the enterprise. It therefore follows the Pareto principle, which states that most effects come from relatively few causes [12]; in clear, a change action correctly targeted at 20% can solve 80% of the problems. Benchmarking the results for each enterprise against the best practices/standards of the branch will then indicate the economic potential for the investment in each specific IScategory. The proposed tool therefore underlies Metcalfe’s law, which states that the value Copyright © 2007 The Authors

of a network is proportional to the square of the number of users of the system [13], i.e. the value of the tool increases with the total number users of the tool.

Figure 1: Strategic IS-options

6.

An Exploratory Case Study with a Swiss SME

The decision-support tool described in the previous section has been applied in an exploratory case study to a Swiss SME of the transportation sector. This company offers three types of products and services: transportation and delivery of goods; collection of garbage buckets and, finally, exploitation of a gravel mine, from which they sell gravel to private and corporate customers. The enterprise employs 6 administrative workers and 18 truck drivers; it has about 4500 customers, one of which represents 30% of the enterprise’s sales turnover. Two major information systems have been introduced in recent years: 1. A Financial Management System (in 2003): This information system pertains to the third category of our IS-classification (Office Automation Systems OAS) and offers management facilities for salaries, invoicing, order listing and reporting. Thanks to this system, manual tasks such as sorting delivery notes, entering data (for recurrent tasks), copying files, calculating totals or verifying amounts are carried out automatically. In addition, the system also brings about qualitative benefits, since it increases transparency for the management by offering the possibility to carry out analytical requests from the database according to various factors such as “per customer”, “per site”, “per product”, “per unit” and so forth; the results of these requests can then be compared to those of the previous years. 2. A Geographical Localization System (in 2005): This IS belongs to the category number 9 (Strategic Information Systems SIS); it allows optimizing tasks and travel miles across the company by coordinating priorities, calculating distances and travel times and indicating the itineraries to follow for all engaged trucks. The truck drivers easily access the system via a touch screen where they consult the next tasks. The system also contributes to increase the overall organizational transparency by offering the possibility to track & trace real-time the position of each truck of the company, since they are all displayed on one map with their corresponding orders/tasks. The IS Cost Ratio is highly sector-depending. Due to an average of IT expenses close to one percent in the transportation branch, the x-axis values on our diagram stretch out over one and a half. The years following these investments, the company manager registered the following average financial impacts that can be attributed to these investments: Copyright © 2007 The Authors

According to this table, the first acquisition (financial management system) has no particular impact on the product value-added and on the customer relationship. In return, it has a significant impact on the operational cost savings (+17%) and a positive return on investment (+4%). Table 2: The Financial Impacts of the IS-Investment Total IS Costs/Total Expenses 1) Transaction Processing Systems (TPS) 2) Management Information Systems (MIS) 3) Office Automation Systems (OAS) 4) Decision Support Systems (DSS) 5) Expert Systems (ES) 6) Group Support Systems (GSS) 7) Knowledge Work Systems (KWS) 8) Executive Information Systems (EIS) 9) Strategic Information Systems (SIS)

Product value-added Customer relationship (PVA) (CR)

Infrastructure / operations (IO)

Financials (FI)

Increase/decrease of product margin in %

Marginal sales turnover increase/decrease in %

Operational cost savings in %

Net return on investment (%) (= Benefits of the period / Invested capital)*100)

0,930%

0

0

17

4

1,125%

30

10

25

12

The second investment (geographical localization system) has the most significant impact on the product value-added (+30%) and on the operational cost savings (+25%); in revenge, although its impact on the sales turnover (+5%) and the return of the investment (+12%) are more limited, they still remain positive. These results lead to the strategies as represented in Figure 2.

Figure 2: The IS-Cockpit for the Enterprise in our Case Study

Both IS results fall into the quadrant A2 for all four dimensions. Thus according to our model it is recommended to further invest in these systems (particularly accentuated for the geographical localization system), since – although this may require some cash – it is worthwhile considering the high financial return it represents. According to the enterprise’s weakness (i.e. in one the four dimensions), it can apply its efforts on that information system which most significantly affects the critical dimension. Benchmarking these results against competitors of the same branch would now indicate whether these results are representative for the branch and whether competitors obtained higher/lower financial returns from identical IS-investments.

Copyright © 2007 The Authors

7.

Conclusions and Recommendations

The decision-support tool presented in this paper proposes a method for systematically decomposing the strategic problem of defining unambiguous IS-priorities into clearly defined elements, by depicting all potential alternatives in a scatter diagram. The tool thereby ensures consistency in the chief information officers’ IS-investment decisions. In clear, it aims at providing support to managers at small and midsize enterprises by recommending appropriate decision-making alternatives, i.e. to invest, to milk or to outsource/drop specific IS-categories. The exploratory test of the tool in a case study with a Swiss SME confirmed its usability and applicability, mainly because it reduces the decision-making complexity by clustering the decision elements according to clearly identifiable characteristics. But, since the tool is based on a benchmark approach, its value is – as of any shared system – proportional to the number of users of the system. Therefore, a next step in this research will be to test the tool with a significant population of SMEs and to develop an electronic application that will be set up on a web platform at the online disposal of SMEs. In a further step, the tool can then be extended to other types of technologies (not exclusively information systems), to other contexts (not exclusively SMEs) and to other countries (not exclusively Switzerland).

Acknowledgments We would like to gratefully acknowledge Prof. Antoine Perruchoud, the initiator of itransformation RCSO Project[14], a source of inspiration through our pathway, for his help and support during planning and accomplishment of the experiment, especially when things became critical.

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